Topic profile query creation

ABSTRACT

A topic profile may be generated based on several words/phrases. The topic profile may include social media content items such as a social media post from a variety of social media sources. The topic profile may be presented to a user via a user interface that displays the one or more included/excluded words/phrases that may form the basis of a query for the topic profile. The user interface may display one or more representative social media content items and/or a word cloud of words/phrases related to the query. A user may select one or more words/phrases in the word cloud and/or one or more social media content items to be included in and/or excluded from the topic profile. The implementations disclosed herein may allow rapid filtering of a potentially large group of content items from potentially disparate social media sources.

BACKGROUND

Some web browser search engines attempt to guess what a user issearching for as a user enters a keyword. For example, in response to aquery such as “How do I” the search engine may make suggestions based onthe user's search history, a user profile, and/or the most popularsearches associated with the query. A web search engine may be directedtoward efficiently locating content for a user utilizing as few ofsearch terms as possible. For example, a conventional web search enginemay receive a single word or phrase as a query and return a top ten listas a result. A user may typically select one of the first results shownon the first page. This approach may not be suitable for a businessseeking to analyze its presence and response by users on social mediawebsites.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are included to provide a furtherunderstanding of the disclosed subject matter, are incorporated in andconstitute a part of this specification. The drawings also illustrateimplementations of the disclosed subject matter and together with thedetailed description serve to explain the principles of implementationsof the disclosed subject matter. No attempt is made to show structuraldetails in more detail than may be necessary for a fundamentalunderstanding of the disclosed subject matter and various ways in whichit may be practiced.

FIG. 1 is an example of a word cloud displayed via the user interface asdisclosed herein.

FIG. 2 is an example of the user interface and a preview pane that maydisplay representative social media content items as disclosed herein.

FIG. 3 is an example process for generating and/or updating a topicprofile.

FIG. 4 is an example overview of a system that includes a databaseoperationally coupled to a processor that can generate and update atopic profile as disclosed herein.

FIG. 5 shows a computer according to an implementation of the disclosedsubject matter.

FIG. 6 shows a network configuration according to an implementation ofthe disclosed subject matter.

DETAILED DESCRIPTION

An implementation of the disclosed invention can dynamically anditeratively generate and maintain a topic profile based on the detectedfrequency of keywords in social media posts. The keywords can beselected by a user to tailor the topic profile as desired. When a userselects a keyword, a new search of social media posts can be performedbased on the selected keyword and new search results can be generated. Anew set of keywords can be derived from the new search results and canbe shown to the user for further review and selection. In this way, auser can iteratively build a focused set of keywords and search resultsto see how a given topic is being treated in social media posts.

Instead of experimenting with isolated search queries, a user may seewhat the most common and/or important terms are, add/remove them easily,and see the results in real time. Utilizing the disclosed system, a usercan view one or more posts consistent with the topic profile as itevolves and may perform analytics on the matching posts. A topic profilemay include, for example, hundreds or thousands of words/phrases, and atleast some content from one or more social media content items thatcorrespond to the words/phrases that are both selected and/or related tothe selected words/phrases. The topic profile may become more complexover time. A topic profile may be generated by first receiving a keywordsuch as a company name or a brand name. The system may return a wordcloud that may represent the most common words/phrases found in thesocial media content items that are returned in response to the query. Auser may then select words from the word cloud to include and/orexclude. As words are added/excluded, a user may receive a preview ofspecific posts that will be matched by the current topic profile. Theuser could simply click “like” and “dislike” buttons on the specificposts and, in response, the system may add and/or remove relevant wordsto or from topic profile. A clustering algorithm may be applied tosocial media content items matching the topic profile to cluster each ofthe content items (e.g., posts). One post may be selected to representthe each cluster and presented as a preview for the user. A user maythen add and/or remove a post. One or more words/phrases that are notcurrently selected by the topic profile but that are determined to befrequent within the cluster represented by a liked post may be added tothe topic profile or presented to the user as words to be included inthe topic profile.

In some instances, a business may wish to manage content, such as thatprovided by social media sites, that mentions the business or productsand/or services provided by the business. As disclosed herein, a queryutilizing a single word or phrase may be utilized to generate a wordcloud with the most commonly associated words and phrases related to theoriginal single word or phrase. The size of the word or phrase shown inthe word cloud may indicate how related the word or phrase is to theoriginal query and/or how frequently the word or phrase is contained inthe same body of text as the original query. For example, a user mayquery social media posts for the word “Salesforce” and the system maydisplay words related to “Salesforce” to the user in a word cloud.Common words such as “the,” “a,” “and,” etc. may be filtered out fromthe word cloud. One of the more prominent phrases in the word cloud maybe “cloud computing” that, upon the word selecting the phrase causes theword cloud to be updated to include “Salesforce” and “cloud computing.”Thus, a topic profile may be generated that may include thousands ofwords, some of which a user has directed to be included in the search.Similarly, the topic profile may exclude words for which an instructionhas been received to be excluded. The user interface may show one ormore of the word cloud corresponding to the topic profile and socialmedia posts related to the topic profile. Continuing the previousexample, a social media post may be shown that includes the word“Salesforce” and the phrase “cloud computing in close proximity thereto.This may provide a business, for example, with the ability to filterthrough a large volume database of social media content items to obtaina specific topic profile and the resultant social media posts from thetopic profile may be separately analyzed for their respective features(e.g., the demographics of the users).

An example of a word cloud display via a user interface is provided inFIG. 1. The initial query may be for the word “Apple” as shown inFIG. 1. The user interface 110 may display only the most relevant and/orfrequent words related to the original query, “Apple” 120 For example,the word “computer” may not be shown in the example word cloud becauseit is below a threshold frequency for the available social media contentitems. Social media content items may refer to, for example, a socialmedia post, a website, an article, a blog, a picture, a video, etc.Typically, in a social media website a user is connected through anonline interface to one or more friends or businesses, thereby enablingthe user to share content items with the one or more friends and/orbusinesses. As shown in FIG. 1, the user interface 110 may displaysocial media content items (e.g., posts) 130 in addition to the wordcloud 140. The posts 130 shown in the user interface 110 may reflectexamples of posts 130 containing the words in the word cloud 140. Socialmedia content items may be selected for display in the user interfacebased on relevancy, random selection, frequency of the appearance ofwords deemed related to the original query, time of posting, location,popularity of the user posting, etc. For example, the prevalence ofselected keywords in the social media content items may be determinedand the selected keywords may be ranked according to their frequency.That is, if the keywords are AAA, BBB, CCC, and DDD, the frequency ofthose four words in a single post among all of the social media sourcesmay be 2%. The frequency for AAA, BBB, and CCC may be 20% and AAA, CCC,and DDD may be 10%. Although the posts containing the four keywords arerarer than those containing three keywords, the four keyword-containingposts may be selected for presentation in the user interface becausethey contain all of the words.

In the example provided in FIG. 1, each social media content item 130also shows a “+” 150 and a “−” 155 symbol which may have configurablefunctions. In some instances, a user may include a post by selecting the“+” 150 symbol or exclude a post by selecting the “−” 155 symbol. Byelecting to include a social media content item, the system may includeany of the words in the post that are also represented in the wordcloud. In some configurations, selecting the “+” 150 button may causethe system to save the post so that a user may return to it later.Selecting the “−” 155 button may remove the post from the userinterface. The system may alter the user interface to replace the postwith another social media content item (e.g., another post in thisexample). The system may receive a selection of one or more of the wordsin the word cloud and update the word cloud and/or the social mediacontent items displayed once the “refresh” button is selected.

A user may elect to save the topic profile that is generated by theinclusion/exclusion of one or more words relative to the query and/orsocial media content items. For example, in FIG. 2, the user interface210 shows an indication of the topic profile that is based on a query220 that includes the words “APPLE,” “IPHONE,” and “IPAD”. The userinterface 210 may display to the user a variety of controls with which auser may modify the topic profile. For example, the user interface 210may provide a selectable list of social media sources 230, a region 240,and/or a language 250. Data indicating the most prevalent words/phrasesassociated with the query may be displayed 260. As shown in FIG. 2, eachword/phrase 260 may be accompanied by an indication of its frequencybased on words/phrases included in the query. A user may modify thequery 220 by including/excluding terms and the user interface 210 may bedynamically updated. For example, as a user adds or removes keywordsfrom the topic profile to form a modified query, the system may querythe database and regenerate a word cloud and/or an indication of themost related and/or frequent words based on the modified query. The userinterface may be updated to reflect the results of the modified querysuch as displaying social media content items that are returned as aresult of the modified query, displaying an updated word cloud, and/ordisplaying an updated list of suggested words/phrases that are relatedand/or frequent among the social media content items returned based onthe modified query.

The user interface may display posts 270 corresponding to the topicprofile. Posts 270 may be presented from one or more social mediasources 230 and each of the social media sources 230 may have a distinctpost type. For example, one social media source may limit a user to acertain number of characters while another social media source may allowa user to include photos and/or videos in addition to text in a post. Insome configurations the topic profile shown in the user interface mayshow all social media content items associated with the query selected.For example, in the preview pane shown in FIG. 2, social media posts areshown for the selected query and filter options.

In some instances a representative post of a group of posts may beselected to be included in the topic profile. A clustering or machinelearning algorithm may be applied to the group of posts to ascertain themost frequent words/phrases in the group of posts. The user interface,for example, may update a word cloud to reflect the most frequentwords/phrases. Posts may be clustered using known multi-objectiveoptimization techniques such as connectivity-based clustering(hierarchical clustering), centroid-based clustering, distribution-basedclustering, intensity-based clustering, etc. For example, incentroid-based clustering (also known as k-means clustering), k clustercenters may be found and each post can be assigned to the nearestcluster center so that the square distances to the cluster areminimized. As another example, a topic profile may be based on wordsApple, iPhone, and iPad. The word cloud may indicate that the mostfrequently found words/phrases in the social media content itemsreturned by the topic profile are photos, Samsung, and camera. A usermay select a representative post of a group of posts for the wordrepresented by photos to be included in the topic profile. The wordcloud may be updated to indicate that the most frequently representedwords/phrases are, in order of the most frequent to least frequent,resolution, focal length, megapixel, and camera. Thus, the system mayrapidly generate a topic profile with relevant words/phrases based onthe clustering of social media content items. A new topic cloud may begenerated and saved based on the selected word/phrases and/or socialmedia sources.

Implementations disclosed herein may provide a quick response ofreal-time data. For example, the time frame for which social mediacontent items may be retrieved and/or queried may be limited to a threehour period, such as the most recent three hour period or a given threehour period in the past. Limiting the time frame to a narrow window(e.g., less than a twenty four hour period of time) may permit thedatabase to quickly provide a response to a user query. Limiting theperiod of time can reduce the number of content items that the systemmust search or analyze. It can also be used to ensure that stale or outof date content items are not used to generate the topic profile, modifythe word cloud, etc. The time frame may be specified using a time framethreshold. When a user switches from one social media source to a secondsocial media source, the database can quickly retrieve and display theresults of the query in the user interface.

In an implementation, an example of which is provided in FIG. 3, a firstquery may be received at 310. The query may be received in the form of asingle word or phrase such as a brand name. One or more social mediacontent items associated with the first query may be identified at 320.A social media content item may refer to, for example, a website, anarticle, a blog, and a social media post. The social media content itemmay include one or more images, audio, video, and/or metadata. The querymay be received by a processor connected to one or more databases onwhich the social media content items are stored. The query may besubmitted via a user interface operating on a client computer operatedby the user. One or more words may be identified as matching and/orbeing related to the query at 330. Each word that is identified asmatching or being related to the query may be contained in each of thesocial media content items. For example, a query shown in FIG. 2 may be“Apple” and related words may be reflected in a word cloud such as“phone” or “iPad.”

A topic profile may be generated based on the query at 340. The topicprofile may include the query, one or more social media content itemsassociated with the query (e.g., social media posts). A user interfacemay be displayed at 350 and may include a word cloud as described aboveand shown in the example provided in FIG. 1. The word cloud may showonly a portion of the total words identified at 330 as being relatedand/or matching the query. Words may be selected for display becausethey appear at a frequency above a threshold value. The threshold valuemay be based on the configuration of the user interface. For example,the user interface may be configured to have a specified area withinwhich it may display words related to the query. If the number ofrelated words identified at 330 exceeds the available area of the userinterface, the user interface may not display a number of the leastfrequent words identified in the query such that the available area ofthe user interface is filled with the most frequently appearingwords/phrases. Further, because the size of the words/phrases in theword cloud may vary based on the frequency and/or relation (e.g., howwell matched) of the word to the query, the system may compute words tobe displayed on the size of the words with respect to the word cloud. Asdescribed earlier, the user interface may include a portion of thesocial media content items corresponding to the words shown in the wordcloud at 340. As described earlier, a clustering algorithm may beapplied to the social media content items and a representative contentitem for each cluster may be selected for display in the user interface.

A selection of a word/phrase shown in the word cloud may be received at350. The selection may be received by selecting a positive indicatorthat is shown on each word. For example, the user interface may show a“+” or “−” sign when a user hovers a mouse pointer over a word. If theuser selects the “+” symbol, it may be received by the system as apositive indicator, that is, that the user would like to include theword in the topic profile and/or modify the user interface based on thetopic profile with the included word. Conversely, if the user selectsthe “−” symbol, the topic profile may exclude the word. Theinclusion/exclusion of one or more words/phrases may be reflected in thesocial media content items shown in the user interface. In someconfigurations, a user may select one or more words/phrases to beincluded in topic profile by selecting one of the social media contentitems. For example, a user may select a “+” symbol displayed on a socialmedia post that is displayed as a representative post of a cluster ofposts. The representative post may have one or more words/phrases thatare highlighted as shown by the emboldened words in FIG. 2, for example.The emboldened words may reflect the words/phrases by which the clusteris represented. For example, the highlighted or otherwise indicatedwords may be those words that are most frequent in the cluster of posts.As another example, highlighted words/phrases may reflect those wordsthat appear within a proximity of other related words. In one cluster,the words AAA, BBB, and CCC all may appear within ten words whereas inanother cluster, the words AAA, BBB, and CCC all may appear within fiftywords of one another. Thus, when a user elects to include therepresentative post, the topic profile may receive the positiveindication as an instruction to include the highlighted words/phrases. Auser may subsequently modify the topic profile to include and/or excludeone or more words.

A second query may be generated or received based on original query(e.g., the key word that initially formed the topic profile) and thosewords/phrases that were identified as being related thereto at 360. Thesecond query may be received by the processor connected to one or moredatabases on which the social media content items are stored. The topicprofile may be updated based on the result of executing the second queryby the process at 370. Updating the topic profile may refer toidentifying one or more social media content items associated with thesecond query. The resultant identified content items, or arepresentation thereof, may be displayed to in the user interface. Theword cloud may be updated to reflect the updated topic profile.

At any stage of updating the topic profile, the resultant social mediacontent items may be filtered by one or more attributes such aslanguage, social media source, region, demographic, etc. Analytics maybe generated for resultant social media content items returned as thetopic profile is refined. For example, a topic profile may result in onehundred posts with three distinct clusters among the one hundred posts.For each cluster, a user may view the age, gender, frequency of theselected words/phrases in the posts, etc. In some configurations, a usermay elect to view content items for the topic profile for a defined timeframe. For example, a user may desire to view social media content itemsfor every Monday in the month of July. Further, analytic data may belimited to a particular time frame.

In an implementation, a system is disclosed that includes a database 410for storing one or more social media content items. An example of thesystem is provided in FIG. 4. Social media content items may beprovided, for example, by social media sources 402, 404, 406. In someconfigurations, the system may utilize a web crawler to obtain contentmedia items. For example, a content aggregator site in which registeredusers post content (e.g., news articles or user generated content) maybe frilly accessible by a web crawler. During the ingestion of contentmedia items, the data may be stored according to rules defined by anextensible mark-up language such as XML.

A processor may be communicatively coupled to the database. Theprocessor 420 may be configured to receive a query from a client device430 and identify related words/phrases to the query. The processor 420may be configured to send the results of the query to a client computer430. The client computer 430 may receive the search results by a userinterface provided by an application 425 operating on the clientcomputer 430. In some configurations, the user interface may be providedby a web page that may be hosted by the system. A user may make aselection of one or more content items and/or words/phrases that havebeen identified and provided in response to the query via the userinterface. The selection may be received by the processor 420 and one ormore social media content items. A topic profile may be generated by theprocessor 420 based on the query and it may include the one or moresocial media content items as described earlier. In some configurations,a snapshot of the one or more content items may be stored in thedatabase 410. For example, the system may be configured to retrievesocial media content items for a specific timeframe and a topic profilemay be stored for each timeframe specified.

The processor 420 may be configured to update the topic profile based ona selection of one or more words/phrases and/or social media contentitems. A user may manually type in a word/phrase to be included in thetopic profile, for example, if the word/phrase is not presented in theuser profile.

The system disclosed herein may be implemented as a multi-tenant system.The system may include a server that can generate one or more virtualapplications based on data stored in a common database shared betweenthe tenants. Each virtual application may provide access to data in thedatabase for each of the one or more tenants utilizing the system. Atenant may refer to a group of users that shares access to common datawithin a database. A tenant may represent customers, customerdepartments, business or legal organizations, and/or any other entitiesthat maintain data for particular sets of users. A tenant may, forexample, request social media posts, metadata, and/or analytics providerdata. Although multiple tenants may share access to a common server anddatabase, the particular data and services provided from the system toeach tenant can be securely isolated from those provided to othertenants. The multi-tenant architecture therefore allows different setsof users to share functionality without necessarily sharing each other'sdata. Similarly, the appearance of each tenant's interface with thesystem may be unique.

The results provided in response to a search query may obtained in atleast two distinct manners. In one configuration, for each word that isadd and/or removed, the system may query the entire database of socialmedia content items and update the topic profile accordingly. In asecond configuration, the system may perform a hierarchical search inwhich the system may query the social media content items returned froma previous query. For example, a user may enter a search term such as“Apple.” The system may return the most popular and relevant words as“iPhone,” “iPad,” and “camera.” The total number of content itemsreturned for the term “Apple” may be three million in the lasttwenty-four hours from among the total number of social media contentitems in the database. If the user elects to add “iPad” to the query,the system may query only the three million content items returned inthe query for “Apple”. This may, for example, yield five hundredthousand posts with “camera” being the most common and/or related termin those posts. If the user further adds the term “camera” to the query,the system may return one hundred thousand of the posts from the fivehundred thousand that include both “Apple” and “iPad.” If the userremoves the term “iPad” from the query, the system may query the threemillion posts returned from that query. The result may be one and a halfmillion posts, some of which (e.g., five hundred thousand) will containthe term “iPad.” The most prevalent term, however, may be “iPhone.”Thus, the order of the terms in topic profile may provide differentsubsets of data. Two topic profiles that contain the same search terms,but in different order may, therefore, result in differentrepresentations of social media content items.

Implementations of the presently disclosed subject matter may beimplemented in and used with a variety of component and networkarchitectures. FIG. 5 is an example computer 20 suitable forimplementations of the presently disclosed subject matter. The computer20 includes a bus 21 which interconnects major components of thecomputer 20, such as a central processor 24, a memory 27 (typically RAM,but which may also include ROM, flash RAM, or the like), an input/outputcontroller 28, a user display 22, such as a display screen via a displayadapter, a user input interface 26, which may include one or morecontrollers and associated user input devices such as a keyboard, mouse,and the like, and may be closely coupled to the I/O controller 28, fixedstorage 23, such as a hard drive, flash storage, Fiber Channel network,SAN device, SCSI device, and the like, and a removable media component25 operative to control and receive an optical disk, flash drive, andthe like.

The bus 21 allows data communication between the central processor 24and the memory 27, which may include read-only memory (ROM) or flashmemory (neither shown), and random access memory (RAM) (not shown), aspreviously noted. The RAM is generally the main memory into which theoperating system and application programs are loaded. The ROM or flashmemory can contain, among other code, the Basic Input-Output system(BIOS) which controls basic hardware operation such as the interactionwith peripheral components. Applications resident with the computer 20are generally stored on and accessed via a computer readable medium,such as a hard disk drive (e.g., fixed storage 23), an optical drive,floppy disk, or other storage medium 25.

The fixed storage 23 may be integral with the computer 20 or may beseparate and accessed through other interfaces. A network interface 29may provide a direct connection to a remote server via a telephone link,to the Internet via an Internet service provider (ISP), or a directconnection to a remote server via a direct network link to the Internetvia a POP (point of presence) or other technique. The network interface29 may provide such connection using wireless techniques, includingdigital cellular telephone connection, Cellular Digital Packet Data(CDPD) connection, digital satellite data connection or the like. Forexample, the network interface 29 may allow the computer to communicatewith other computers via one or more local, wide-area, or othernetworks, as shown in FIG. 6.

Many other devices or components (not shown) may be connected in asimilar manner (e.g., document scanners, digital cameras and so on).Conversely, all of the components shown in FIG. 5 need not be present topractice the present disclosure. The components can be interconnected indifferent ways from that shown. The operation of a computer such as thatshown in FIG. 5 is readily known in the art and is not discussed indetail in this application. Code to implement the present disclosure canbe stored in computer-readable storage media such as one or more of thememory 27, fixed storage 23, removable media 25, or on a remote storagelocation.

FIG. 6 shows an example network arrangement according to animplementation of the disclosed subject matter. One or more clients 10,11, such as local computers, smart phones, tablet computing devices, andthe like may connect to other devices via one or more networks 7. Thenetwork may be a local network, wide-area network, the Internet, or anyother suitable communication network or networks, and may be implementedon any suitable platform including wired and/or wireless networks. Theclients may communicate with one or more servers 13 and/or databases 15.The devices may be directly accessible by the clients 10, 11, or one ormore other devices may provide intermediary access such as where aserver 13 provides access to resources stored in a database 15. Theclients 10, 11 also may access remote platforms 17 or services providedby remote platforms 17 such as cloud computing arrangements andservices. The remote platform 17 may include one or more servers 13and/or databases 15.

More generally, various implementations of the presently disclosedsubject matter may include or be implemented in the form ofcomputer-implemented processes and apparatuses for practicing thoseprocesses. Implementations also may be implemented in the form of acomputer program product having computer program code containinginstructions implemented in non-transitory and/or tangible media, suchas floppy diskettes, CD-ROMs, hard drives, USB (universal serial bus)drives, or any other machine readable storage medium, wherein, when thecomputer program code is loaded into and executed by a computer, thecomputer becomes an apparatus for practicing implementations of thedisclosed subject matter. Implementations also may be implemented in theform of computer program code, for example, whether stored in a storagemedium, loaded into and/or executed by a computer, or transmitted oversome transmission medium, such as over electrical wiring or cabling,through fiber optics, or via electromagnetic radiation, wherein when thecomputer program code is loaded into and executed by a computer, thecomputer becomes an apparatus for practicing implementations of thedisclosed subject matter. When implemented on a general-purposemicroprocessor, the computer program code segments configure themicroprocessor to create specific logic circuits. In someconfigurations, a set of computer-readable instructions stored on acomputer-readable storage medium may be implemented by a general-purposeprocessor, which may transform the general-purpose processor or a devicecontaining the general-purpose processor into a special-purpose deviceconfigured to implement or carry out the instructions. Implementationsmay be implemented using hardware that may include a processor, such asa general purpose microprocessor and/or an Application SpecificIntegrated Circuit (ASIC) that implements all or part of the techniquesaccording to implementations of the disclosed subject matter in hardwareand/or firmware. The processor may be coupled to memory, such as RAM,ROM, flash memory, a hard disk or any other device capable of storingelectronic information. The memory may store instructions adapted to beexecuted by the processor to perform the techniques according toimplementations of the disclosed subject matter.

The foregoing description, for purpose of explanation, has beendescribed with reference to specific implementations. However, theillustrative discussions above are not intended to be exhaustive or tolimit implementations of the disclosed subject matter to the preciseforms disclosed. Many modifications and variations are possible in viewof the above teachings. The implementations were chosen and described inorder to explain the principles of implementations of the disclosedsubject matter and their practical applications, to thereby enableothers skilled in the art to utilize those implementations as well asvarious implementations with various modifications as may be suited tothe particular use contemplated.

The invention claimed is:
 1. A method for creating a topic profilecomprising: receiving a first search topic; identifying a firstplurality of social posts associated with the first search topic,wherein the first plurality of social posts are a result of executingthe first search topic; identifying, from among the first plurality ofsocial posts, a first set of one or more related keywords, wherein eachkeyword in the first set is referenced in at least one social post fromamong the plurality of social posts; generating a data set based on thefirst search topic, wherein the data set comprises the first searchtopic, the first plurality of social posts, and the first set of one ormore related keywords; analyzing at least a portion of the firstplurality of social posts to generate at least one analysis; anddisplaying a user interface comprising: a phrase cloud based on the dataset, wherein the phrase cloud comprises the first search topic and thefirst set of one or more related keywords, at least a portion of thefirst plurality of social posts, and the at least one analysis.
 2. Themethod of claim 1, wherein the at least one analysis is based ondemographics of persons associated with the social posts in the at leasta portion of the first plurality of social posts.
 3. The method of claim1, wherein the at least one analysis is based on the ages of personsassociated with the social posts in the at least a portion of the firstplurality of social posts.
 4. The method of claim 1, wherein the atleast one analysis is based on the genders of persons associated withthe social posts in the at least a portion of the first plurality ofsocial posts.
 5. The method of claim 1, wherein the at least oneanalysis is based on the frequency of words or phrases in the socialposts in the at least a portion of the first plurality of social posts.6. The method of claim 1, wherein the at least one analysis is based onlocations associated with the social posts in the at least a portion ofthe first plurality of social posts.
 7. The method of claim 1, whereinthe at least one analysis is based on languages of the social posts inthe at least a portion of the first plurality of social posts.
 8. Themethod of claim 1, wherein the at least one analysis is based on thesocial media sources of the social posts in the at least a portion ofthe first plurality of social posts.
 9. The method of claim 1, furthercomprising receiving a time frame, and wherein the at least a portion ofthe first plurality of social posts analyzed to generate the at leastone analysis further comprises social posts from within the receivedtime frame.
 10. The method of claim 1, further comprising automaticallygrouping similar social posts among the first plurality of content itemsusing text clustering, and wherein displaying at least a portion of thefirst plurality of content items comprises displaying a representativecontent item from each group of similar content items, wherein therepresentative content item represents a group of similar content items.11. The method of claim 10, wherein the at least a portion of theplurality of social posts analyzed to generate the at least one analysisis from a group of similar social posts.
 12. A system for creating atopic profile comprising: a database for storing a plurality of socialposts; a processor communicatively coupled to the database, theprocessor configured to: identify a first plurality of social postsassociated with the first query, wherein the first plurality of socialposts are a result of executing the first query; identify, from amongthe first plurality of social posts, a first set of one or more relatedkeywords, wherein each keyword in the first set is referenced in atleast one social post from among the plurality of social posts; generatea data set based on the first query, wherein the data set comprises thefirst query, the first plurality of social posts, and the first set ofone or more related keywords; analyze at least a portion of the firstplurality of social posts to generate at least one analysis; and displaya user interface comprising: a phrase cloud based on the data set,wherein the phrase cloud comprises the first query and the first set ofone or more related keywords, at least a portion of the first pluralityof social posts, and the at least one analysis.
 13. The system of claim12, wherein the at least one analysis is based on demographics ofpersons associated with the social posts in the at least a portion ofthe first plurality of social posts.
 14. The system of claim 12, whereinthe at least one analysis is based on the ages of persons associatedwith the social posts in the at least a portion of the first pluralityof social posts.
 15. The system of claim 12, wherein the at least oneanalysis is based on the genders of persons associated with the socialposts in the at least a portion of the first plurality of social posts.16. The system of claim 12, wherein the at least one analysis is basedon the frequency of words or phrases in the social posts in the at leasta portion of the first plurality of social posts.
 17. The system ofclaim 12, wherein the at least one analysis is based on locationsassociated with the social posts in the at least a portion of the firstplurality of social posts.
 18. The system of claim 12, wherein the atleast one analysis is based on languages of the social posts in the atleast a portion of the first plurality of social posts.
 19. The systemof claim 12, wherein the at least one analysis is based on the socialmedia sources of the social posts in the at least a portion of the firstplurality of social posts.
 20. The system of claim 12, wherein theprocessor is further configured to receive a time frame, and wherein theat least a portion of the first plurality of social posts analyzed togenerate the at least one analysis further comprises social posts fromwithin the received time frame.
 21. The system of claim 12, wherein theprocessor is further configured to automatically group similar socialposts among the first plurality of content items using text clustering,and to further display at least a portion of the first plurality ofcontent items by displaying a representative content item from eachgroup of similar content items, wherein the representative content itemrepresents a group of similar content items.
 22. The system of claim 21,wherein the at least a portion of the plurality of social posts analyzedto generate the at least one analysis is from a group of similar socialposts.